Teaching Real Data Interpretation with Models (TRIM): Analysis of Student Dialogue in a Large-Enrollment Cell and Developmental Biology Course

Persistent Link:
http://hdl.handle.net/10150/617001
Title:
Teaching Real Data Interpretation with Models (TRIM): Analysis of Student Dialogue in a Large-Enrollment Cell and Developmental Biology Course
Author:
Zagallo, P.; Meddleton, S.; Bolger, M. S.
Affiliation:
Univ Arizona, Dept Mol & Cellular Biol
Issue Date:
2016-05-18
Publisher:
AMER SOC CELL BIOLOGY
Citation:
Teaching Real Data Interpretation with Models (TRIM): Analysis of Student Dialogue in a Large-Enrollment Cell and Developmental Biology Course 2016, 15 (2):ar17 Cell Biology Education
Journal:
Cell Biology Education
Rights:
© 2016 P. Zagallo et al.CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).
Collection Information:
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
Abstract:
We present our design for a cell biology course to integrate content with scientific practices, specifically data interpretation and model-based reasoning. A 2-yr research project within this course allowed us to understand how students interpret authentic biological data in this setting. Through analysis of written work, we measured the extent to which students' data interpretations were valid and/or generative. By analyzing small-group audio recordings during in-class activities, we demonstrated how students used instructor-provided models to build and refine data interpretations. Often, students used models to broaden the scope of data interpretations, tying conclusions to a biological significance. Coding analysis revealed several strategies and challenges that were common among students in this collaborative setting. Spontaneous argumentation was present in 82% of transcripts, suggesting that data interpretation using models may be a way to elicit this important disciplinary practice. Argumentation dialogue included frequent co-construction of claims backed by evidence from data. Other common strategies included collaborative decoding of data representations and noticing data patterns before making interpretive claims. Focusing on irrelevant data patterns was the most common challenge. Our findings provide evidence to support the feasibility of supporting students' data-interpretation skills within a large lecture course.
ISSN:
1931-7913
DOI:
10.1187/cbe.15-11-0239
Version:
Final published version
Additional Links:
http://www.lifescied.org/cgi/doi/10.1187/cbe.15-11-0239

Full metadata record

DC FieldValue Language
dc.contributor.authorZagallo, P.en
dc.contributor.authorMeddleton, S.en
dc.contributor.authorBolger, M. S.en
dc.date.accessioned2016-07-15T01:23:13Z-
dc.date.available2016-07-15T01:23:13Z-
dc.date.issued2016-05-18-
dc.identifier.citationTeaching Real Data Interpretation with Models (TRIM): Analysis of Student Dialogue in a Large-Enrollment Cell and Developmental Biology Course 2016, 15 (2):ar17 Cell Biology Educationen
dc.identifier.issn1931-7913-
dc.identifier.doi10.1187/cbe.15-11-0239-
dc.identifier.urihttp://hdl.handle.net/10150/617001-
dc.description.abstractWe present our design for a cell biology course to integrate content with scientific practices, specifically data interpretation and model-based reasoning. A 2-yr research project within this course allowed us to understand how students interpret authentic biological data in this setting. Through analysis of written work, we measured the extent to which students' data interpretations were valid and/or generative. By analyzing small-group audio recordings during in-class activities, we demonstrated how students used instructor-provided models to build and refine data interpretations. Often, students used models to broaden the scope of data interpretations, tying conclusions to a biological significance. Coding analysis revealed several strategies and challenges that were common among students in this collaborative setting. Spontaneous argumentation was present in 82% of transcripts, suggesting that data interpretation using models may be a way to elicit this important disciplinary practice. Argumentation dialogue included frequent co-construction of claims backed by evidence from data. Other common strategies included collaborative decoding of data representations and noticing data patterns before making interpretive claims. Focusing on irrelevant data patterns was the most common challenge. Our findings provide evidence to support the feasibility of supporting students' data-interpretation skills within a large lecture course.en
dc.language.isoenen
dc.publisherAMER SOC CELL BIOLOGYen
dc.relation.urlhttp://www.lifescied.org/cgi/doi/10.1187/cbe.15-11-0239en
dc.rights© 2016 P. Zagallo et al.CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).en
dc.titleTeaching Real Data Interpretation with Models (TRIM): Analysis of Student Dialogue in a Large-Enrollment Cell and Developmental Biology Courseen
dc.typeArticleen
dc.contributor.departmentUniv Arizona, Dept Mol & Cellular Biolen
dc.identifier.journalCell Biology Educationen
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.en
dc.eprint.versionFinal published versionen
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